An intermediate family of ML-navigation methods convert the image into
actionable information (or affordance states), such as local structural
information useful for driving along roadways [1]}
(e.g., distance to vehicles, lane locations, lane marker relative offsets,
etc.). Another example learns to identify forest trails for navigation
guidance [2]}. The output states are used to then
generate a navigation decision. The target application is usually a
restricted form of navigation.
